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A Dataset from an Excel file will store None for any empty cell. In CSV the convention is to not distinguish between ,, and ,"", and treat all empty cells as empty strings. It would be nice to add a feature like that in pandas.read_csv() where ,, is treated as NaN, but None here for symmetry with Excel. I know that toggling the na_filter argument in read_csv() is one way to govern this in pandas.
Anyways, thanks for the useful tool.
The text was updated successfully, but these errors were encountered:
hugovk
changed the title
SUGGESTION - Offer optoin to normalize treatment of missing values
Suggestion: Option to normalize treatment of missing values
Dec 6, 2021
A Dataset from an Excel file will store
None
for any empty cell. In CSV the convention is to not distinguish between,,
and,"",
and treat all empty cells as empty strings. It would be nice to add a feature like that inpandas.read_csv()
where,,
is treated asNaN
, butNone
here for symmetry with Excel. I know that toggling thena_filter
argument inread_csv()
is one way to govern this in pandas.Anyways, thanks for the useful tool.
The text was updated successfully, but these errors were encountered: